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Collision avoidance is critical in multirobot systems. Most of the current methods for collision avoidance either require high computation costs (e.g., velocity obstacles and mathematical optimization) or cannot always provide safety guarantees (e.g., learning-based methods). Moreover, they cannot deal with uncertain sensing data and linguistic requirements (e.g., the speed of a robot should not be large when it is near to other robots). Hence, to guarantee real-time collision avoidance and deal with linguistic requirements, a distributed and hybrid motion planning method, named Fuzzy-VO, is proposed for multirobot systems. It contains two basic components: fuzzy rules, which can deal with linguistic requirements and compute motion efficiently, and velocity obstacles (VOs), which can generate collision-free motion effectively. The Fuzzy-VO applies an intruder selection method to mitigate the exponential increase of the number of fuzzy rules. In detail, at any time instant, a robot checks the robots that it may collide with and retrieves the most dangerous robot in each sector based on the predicted collision time; then, the robot generates its velocity in real-time via fuzzy inference and VO-based fine-tuning. At each time instant, a robot only needs to retrieve its neighbors’ current positions and velocities, so the method is fully distributed. Extensive simulations with a different number of robots are carried out to compare the performance of Fuzzy-VO with the conventional fuzzy rule method and the VO-based method from different aspects. The results show that: Compared with the conventional fuzzy rule method, the average success rate of the proposed method can be increased by 306.5%; compared with the VO-based method, the average one-step decision time is reduced by 740.9%.
This study aimed to analyze the clinical effects of microdissection testicular sperm extraction (micro-TESE) surgery combined with an intracytoplasmic sperm injection (ICSI) regimen in the treatment of non-obstructive azoospermia (NOA) patients with different etiologies. In total, 128 NOA patients participated in this study, in which they received infertility treatment by micro-TESE surgery combined with an ICSI regimen, and all patients were divided into three groups [the Klinefelter syndrome (KS), the idiopathic and the secondary NOA groups]. In addition, the sperm retrieval rate (SRR), fertilization rate, embryo development status and clinical treatment effects were analyzed. Among the 128 NOA patients, the SRR of KS NOA patients was 48.65%, those of idiopathic and the secondary patients were 33.82% and 73.91%, respectively. Regardless of etiologies, there was no correlation with age, hormone value or testicular volume. Further analysis showed that the SRR of the KS group was positively related with testosterone (T) values, and the SRR of the secondary group had a positive relationship with follicle-stimulating hormone or luteinizing hormone values. In the subsequent clinical treatment, the retrieved sperm was subjected to ICSI and achieved good treatment effects, especially in the secondary group, and the implantation rate (55.56%) and clinical pregnancy rate (68.42%) were both higher than those of the idiopathic group (28.75% and 40.00%) and KS group (22.05% and 30.77%). Micro-TESE surgery combined with ICSI insemination is the most effective treatment regimen for NOA patients. The SRR of NOA patients with different etiologies are related to certain specific factors, and micro-TESE surgery seems to be the ideal and only way to have biological children.
The relationship of a diet low in fibre with mortality has not been evaluated. This study aims to assess the burden of non-communicable chronic diseases (NCD) attributable to a diet low in fibre globally from 1990 to 2019.
All data were from the Global Burden of Disease (GBD) Study 2019, in which the mortality, disability-adjusted life-years (DALY) and years lived with disability (YLD) were estimated with Bayesian geospatial regression using data at global, regional and country level acquired from an extensively systematic review.
All data sourced from the GBD Study 2019.
All age groups for both sexes.
The age-standardised mortality rates (ASMR) declined in most GBD regions; however, in Southern sub-Saharan Africa, the ASMR increased from 4·07 (95 % uncertainty interval (UI) (2·08, 6·34)) to 4·60 (95 % UI (2·59, 6·90)), and in Central sub-Saharan Africa, the ASMR increased from 7·46 (95 % UI (3·64, 11·90)) to 9·34 (95 % UI (4·69, 15·25)). Uptrends were observed in the age-standardised YLD rates attributable to a diet low in fibre in a number of GBD regions. The burden caused by diabetes mellitus increased in Central Asia, Southern sub-Saharan Africa and Eastern Europe.
The burdens of disease attributable to a diet low in fibre in Southern sub-Saharan Africa and Central sub-Saharan Africa and the age-standardised YLD rates in a number of GBD regions increased from 1990 to 2019. Therefore, greater efforts are needed to reduce the disease burden caused by a diet low in fibre.
Population suppression is an effective way for controlling insect pests and disease vectors, which cause significant damage to crop and spread contagious diseases to plants, animals and humans. Gene drive systems provide innovative opportunities for the insect pests population suppression by driving genes that impart fitness costs on populations of pests or disease vectors. Different gene-drive systems have been developed in insects and applied for their population suppression. Here, different categories of gene drives such as meiotic drive (MD), under-dominance (UD), homing endonuclease-based gene drive (HEGD) and especially the CRISPR/Cas9-based gene drive (CCGD) were reviewed, including the history, types, process and mechanisms. Furthermore, the advantages and limitations of applying different gene-drive systems to suppress the insect population were also summarized. This review provides a foundation for developing a specific gene-drive system for insect population suppression.
The codling moth Cydia pomonella is a major pest of global significance impacting pome fruits and walnuts. It threatens the apple industry in the Loess Plateau and Bohai Bay in China. Sterile insect technique (SIT) could overcome the limitations set by environmentally compatible area-wide integrated pest management (AW-IPM) approaches such as mating disruption and attract-kill that are difficult to suppress in a high-density pest population, as well as the development of insecticide resistance. In this study, we investigated the effects of X-ray irradiation (183, 366, 549 Gy) on the fecundity and fertility of a laboratory strain of C. pomonella, using a newly developed irradiator, to evaluate the possibility of X-rays as a replacement for Cobalt60 (60Co-γ) and the expanded future role of this approach in codling moth control. Results show that the 8th-day is the optimal age for irradiation of male pupae. The fecundity decreased significantly as the dosage of radiation increased. The mating ratio and mating number were not influenced. However, treated females were sub-sterile at a radiation dose of 183 Gy (20.93%), and were almost 100% sterile at a radiation dose of 366 Gy or higher. Although exposure to a radiation dose of 366 Gy resulted in a significant reduction in the mating competitiveness of male moths, our radiation biology results suggest that this new generation of X-ray irradiator has potential applications in SIT programs for future codling moth control.
Aiming at the problem of low accuracy of robot joint fault diagnosis, a fault diagnosis method of robot joint based on BP neural network is designed. In this paper, the UR10 robot is taken as the research object, and the end pose data of the robot are collected in real time. By injecting different joint errors and changing the sampling frequency, the joint fault database is collected and established, and the BP neural network is used for training to obtain the robot neural network fault diagnosis model. The fault diagnosis model can output the joint fault of the input end pose data. And we analyzed the influence of different joint angle errors and different training sets on the accuracy of joint fault diagnosis of the robot. The results show that when the sampling frequency is 250 Hz, the simulation result of joint fault diagnosis accuracy with the fault degree of 0.5° is 99.17%, and the experimental result is 97.87%. Compared with traditional data-driven methods, it has higher accuracy and diagnostic efficiency, and compared with existing machine learning methods, it also achieves a high accuracy while reducing the network complexity. The effectiveness of the BP neural network robot joint fault diagnosis method is verified by experiments.
Late Palaeozoic igneous rock associations in response to subduction, accretion, and final closure of the eastern Palaeo-Asian Ocean play a significant role in understanding the geodynamic evolution of the southeastern Central Asian Orogenic Belt. Previous studies have identified a Permian arc magmatic belt associated with the southward-dipping subduction of the eastern Palaeo-Asian Ocean along the Solonker–Changchun suture zone. The genetic mechanism and associated geodynamic settings are of great importance in deciphering the evolution of the eastern Palaeo-Asian Ocean. This paper presents zircon U–Pb–Hf isotope and whole-rock geochemical analyses for a suite of magmatic rocks including the early Permian diorite porphyrites (ca. 281.0 Ma), andesites (ca. 276 Ma) and rhyolites (ca. 275 Ma) in the Kulun region. The diorite porphyrites and andesites have high SiO2 and total alkali contents, and low MgO contents and Mg no. values, with enrichments in large ion lithophile elements and depletions in high-field-strength elements. These geochemical characteristics, together with low-Sr and high-Yb contents, a weak concave-upward shape of middle rare earth elements and negative Eu anomalies, suggest that these intermediate igneous rocks were generated by partial melting of amphibolitic lower crust at a crustal depth of 30–40 km. The rhyolites have heterogeneous isotopic compositions, with ϵHf(t) values and TDM2 ages of –20.8 to +0.5 and 3578∼1494 Ma, implying that they were likely derived from partial melting of a mixed source dominated by recycled ancient crust with minor juvenile crustal materials. The rhyolites show potassic affinity with relatively high K2O and very low Na2O, which was attributed to liquid immiscibility of felsic magma and subsequent limited fractional crystallization of plagioclase. The regional igneous associations, metamorphic events, and coeval sedimentary rocks along the Solonker–Changchun suture zone indicate that the early Permian igneous rocks were formed in an active continental arc environment in response to southward subduction of the eastern Palaeo-Asian Ocean.
The COVID-19 pandemic has drastically impacted many aspects of society and has indirectly produced various psychological consequences. This systematic review aimed to estimate the worldwide prevalence of posttraumatic stress disorder (PTSD) in children due to the COVID-19 pandemic, as well as to identify protective or risk factors contributing to child PTSD.
We conducted a systematic literature search in the PubMed, ProQuest, PsycINFO, Embase, Web of Science, WanFang, CNKI, and VIP databases. We searched for studies published between January 1, 2020 and May 26, 2021, that reported the prevalence of child PTSD due to the COVID-19 pandemic, as well as factors contributing to child PTSD. Eighteen studies were included in our systematic review, of which 10 studies were included in the meta-analysis.
The estimated prevalence of child PTSD after the COVID-19 outbreak was 28.15% (95% CI: 19.46–36.84%, I2 = 99.7%). In subgroup analyses for specific regions the estimated prevalence of post-pandemic child PTSD was 19.61% (95% CI: 11.23–27.98%) in China, 50.8% (95% CI: 34.12–67.49%) in the USA, and 50.08% in Italy (95% CI: 47.32–52.84%).
Factors contributing to child PTSD were categorized into four aspects: personal factors, family factors, social factors and infectious diseases related factors. Based on this, we presented a new framework summarizing the occurrence and influence of the COVID-19 related child PTSD, which may contribute to a better understanding, prevention and development of interventions for child PTSD in forthcoming pandemics.
According to a WHO report, the number of patients with coronavirus disease 2019 (COVID-19) has reached 456,797,217 worldwide as of 15 March, 2022. In Wuhan, China, large teams of health-care personnel were dispatched to respond to the COVID-19 emergency. This study aimed to determine the sociodemographic and psychological predictors of resilience among frontline nurses fighting the current pandemic.
A total of 143 nurses were recruited from February 15 to February 20, 2020, to participate in this study. The 10-item Connor-Davidson Resilience Scale and the 21-item Depression Anxiety Stress Scale were used to estimate the participants’ resilience and mental wellbeing.
Results showed that the nurses displayed a moderate resilience level. Their median depression, anxiety, and stress scores were 1, 2, and 3, respectively, which were negatively correlated with resilience. Female gender, being dispatched to Wuhan, and depression levels were the significant predictors of resilience.
The results suggest that particular attention should be given to nurses who were dispatched to Wuhan and who exhibited depression symptoms, and appropriate measures should be taken to boost their resilience.
Nicotine 2,6-dihydroxybenzoate is a nicotine salt that can be used as the nicotine source in tobacco products. X-ray powder diffraction data, unit-cell parameters, and space group for nicotine 2,6-dihydroxybenzoate, C10H15N2⋅C7H5O4, are reported [a = 7.726(8) Å, b = 11.724(3) Å, c = 9.437(1) Å, α = 90°, β = 109.081(3)°, γ = 90°, unit-cell volume V = 802.902 Å3, Z = 2, ρcal = 1.309 g cm−3, and space group P21] at room temperature. All measured lines were indexed and were consistent with the P21 space group.
Subthreshold depression (sD) negatively impacts well-being and psychosocial function and is more prevalent compared with major depressive disorder (MDD). However, as adults with sD are less likely to seek face-to-face intervention, internet-based cognitive-behavioral therapy (ICBT) may overcome barriers of accessibility to psychotherapy. Although several trials explored the efficacy of ICBT for sD, the results remain inconsistent. This study evaluated whether ICBT is effective in reducing depressive symptoms among Chinese adults with sD.
A randomized controlled trial was performed. The participants were randomly assigned to 5 weeks of ICBT, group-based face-to-face cognitive-behavioral therapy (CBT), or a waiting list (WL). Assessments were conducted at baseline, post-intervention and at a 6-month follow-up. The primary outcome measured depressive symptoms using the Center for Epidemiological Studies Depression Scale (CES-D). Outcomes were analyzed using a mixed-effects model to assess the effects of ICBT.
ICBT participants reported greater reductions on all the outcomes compared to the WL group at post-intervention. The ICBT group showed larger improvement on the Patient Health Questionnaire-9 (PHQ-9) at post-intervention (d = 0.12) and at follow-up (d = 0.10), and with CES-D at post-intervention (d = 0.06), compared to the CBT group.
ICBT is effective in reducing depressive symptoms among Chinese adults with sD, and improvements in outcomes were sustained at a 6-month follow-up. Considering the low rates of face-to-face psychotherapy, our findings highlight the considerable potential and implications for the Chinese government to promote the use of ICBT for sD in China.
The sedimentary characteristics and preservation potential of lacustrine carbonates provide fundamental information on climate change. The lacustrine carbonate deposition in the Eocene Dongying Depression was investigated using a combination of mineralogical, petrological and geochemical analyses. Micritic calcite/dolomite, granular calcite, columnar calcite, calcareous shell fragments and reworked detrital calcite were identified. Varying patterns of carbonates (VPC) including lithofacies, geochemical indicators and carbonate distribution were revealed in the Dongying Depression: (i) carbonates hardly precipitate in the nearshore area (average 12 wt %); (ii) carbonate content is high (average 53 wt %) in the shallow lake and (iii) gradually decreases to reach a minimum (average 24 wt %) in the deeper part of the lake. Comparison of VPC in four Holocene lakes (the Qinghai Lake and Barkol Lake in China, Oro Lake in Canada and Montcortès Lake in Spain) with the Dongying Depression suggests that four distinct lake stages were developed, namely the terrigenous clastic/gypsum-rich, carbonate-rich, carbonate-decreasing and carbonate-poor stages. A depositional model of lacustrine carbonates influenced by detrital influx, climate, palaeoproductivity and salinity is developed. This study contributes to the understanding of the genetic mechanisms of lacustrine carbonate deposition to reconstruct environmental changes.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
There is an ongoing debate on whether wine reviews provide meaningful information on wine properties and quality. However, few studies have been conducted aiming directly at comparing the utility of wine reviews and numeric measurements in wine data analysis. Based on data from close to 300,000 wines reviewed by Wine Spectator, we use logistic regression models to investigate whether wine reviews are useful in predicting a wine's quality classification. We group our sample into one of two binary quality brackets, wines with a critical rating of 90 or above and the other group with ratings of 89 or below. This binary outcome constitutes our dependent variable. The explanatory variables include different combinations of numerical covariates such as the price and age of wines and numerical representations of text reviews. By comparing the explanatory accuracy of the models, our results suggest that wine review descriptors are more accurate in predicting binary wine quality classifications than are various numerical covariates—including the wine's price. In the study, we include three different feature extraction methods in text analysis: latent Dirichlet allocation, term frequency-inverse document frequency, and Doc2Vec text embedding. We find that Doc2Vec is the best performing feature extraction method that produces the highest classification accuracy due to its capability of using contextual information from text documents. (JEL Classifications: C45, C88, D83)
Wines are usually evaluated by wine experts and enthusiasts who give numeric ratings as well as text reviews. While most wine classification studies have been based on conventional statistical models using numeric variables, there has been very limited work on implementing neural network models using wine reviews. In this paper, we apply neural network models (CNN, BiLSTM, and BERT) to extract useful information from wine reviews and classify wines according to different rating classes. Using a large collection of wine reviews from Wine Spectator, the study shows that BERT, a neural network framework recently developed by Google, has the best performance. In the two-class classification (90–100 and 80–89), BERT achieves an accuracy of 89.12%, followed by BiLSTM (88.69%) and CNN (88.02%). In the four-class classification (95–100, 90–94, 85–89, and 80–84), BERT yields an 81.57% accuracy, while the other two produce an 80% accuracy. The neural network models in the paper are independent of domain knowledge and thus can be easily extended to other kinds of text analysis. Expanding the limited work on wine text review classification studies, these models are up-to-date and provide valuable additions to wine data analysis. (JEL Classifications: C45, C88, D83)
We report the demonstration of a mid-infrared (MIR) supercontinuum (SC) laser delivering a record-breaking average output power of more than 40 W with a long-wavelength edge up to 3.5 μm. The all-fiberized configuration was composed of a thulium-doped fiber amplifier system emitting a broadband spectrum covering 1.9–2.6 μm with pulse repetition rate of 3 MHz, and a short piece of germania fiber. A 41.9 W MIR SC with a whole spectrum of 1.9–3.5 μm was generated in a piece of 0.2-m-long germania fiber, with a power conversion efficiency of 71.4%. For an even shorter germania fiber (0.1 m), an SC with even higher output power of 44.9 W (corresponding to a conversion efficiency of 76.5%) was obtained, but the energy conversion toward the long-wavelength region was slightly limited. A continuous operation for 1 hour with output power of 32.6 W showed outstanding power stability (root mean square 0.17%) of the obtained SC laser. To the best of the authors’ knowledge, for the first time, this work demonstrates the feasibility of germania fiber on generating a 40-W level MIR SC with high efficiency and excellent power stability, paving the way to real applications requiring high power and high reliability of MIR SC lasers.
As an important index to quantitatively measure the motion performance of a manipulator, motion reliability is affected by many factors, such as joint clearance. The present research utilized a UR10 manipulator as the research object. A factor mapping model for influencing the motion reliability was established. The link flexibility factor, joint flexibility factor, joint clearance factor, and Denavit–Hartenberg (DH) parameters were comprehensively considered in this model. The coupling relationship among the various factors was concisely expressed. Subsequently, the nonlinear response surface method was used to calculate the reliability and sensitivity of the manipulator, which provided an applicable reference for its trajectory planning and motion control. In addition, a data-driven fault diagnosis method based on the kernel principal component analysis (KPCA) was used to verify the motion accuracy and sensitivity of the manipulator, and joint rotation failure was considered as an example to verify the accuracy of the KPCA method. This study on the motion reliability of the manipulator is of great significance for the current motion performance, adjusting the control strategy and optimizing the completion effect of the motion task of a manipulator.
This retrospective study investigated the predictive value of the Controlling Nutritional Status (CONUT) score in patients with intermediate-stage hepatocellular carcinoma (HCC) who received transarterial chemoembolization (TACE). Nomograms were developed to predict progression-free and overall survival (PFS, OS). The medical data of 228 patients with HCC and treated with TACE were collected. The patients were apportioned to 2 groups according to CONUT score: low or high (<4, ≥4). Univariate and multivariate analyses were performed using Cox regression for OS and PFS. OS and PFS were estimated by the Kaplan-Meier curve and compared with the log-rank test. Nomograms were constructed to predict patient OS and PFS. The nomograms were evaluated for accuracy, discrimination, and efficiency. The cut-off value of CONUT score was 4. The higher the CONUT score, the worse the survival; Kaplan-Meier curves showed significant differences in OS and PFS between the low and high CONUT score groups (P = 0·033, 0·047). The nomograms including CONUT, based on the prognostic factors determined by the univariate and multivariate analyses, to predict survival in HCC after TACE were generated. The CONUT score is an important prognostic factor for both OS and PFS for patients with intermediate HCC who underwent TACE. The cut-off value of the CONUT score was 4. A high CONUT score suggests poor survival outcomes. Nomograms generated based on the CONUT score were good models to predict patient OS and PFS.